Imagine a world where AI not only understands language but also possesses a deep, structured understanding of the world's knowledge. This is the promise of merging Large Language Models (LLMs) with Knowledge Graphs (KGs), a hot topic explored at the recent LLM+KG@VLDB'24 Workshop. LLMs excel at understanding language patterns and generating human-like text, but they sometimes fabricate facts or 'hallucinate'. KGs, on the other hand, offer a structured, factual representation of knowledge, like a vast interconnected web of concepts and relationships. Combining these two powerful technologies could create AI systems that are both intelligent and grounded in reality. Researchers discussed how KGs can help LLMs become more accurate and reliable by providing factual grounding and improving reasoning abilities. Conversely, LLMs can enhance KGs by automating their creation, completion, and making them easier to query. The workshop highlighted key data management challenges, such as ensuring data consistency, scalability, and knowledge editing within this merged paradigm. The fusion of LLMs and KGs presents exciting opportunities, from improving AI assistants to revolutionizing fields like healthcare and finance. However, ensuring these powerful AI systems are transparent, fair, and respect privacy remains a crucial challenge for researchers and developers.